AI Engineer; Generative​/Agentic AI

Your mission will be to translate cutting‑edge research into production‑ready solutions, focusing on model compression, system optimisations, and agentic capabilities such as function calling and tool orchestration. Experience with designing secure and reliable agentic workflows, including guardrails and safe tool invocation, is considered a strong plus.

• Optimize LLMs and multimodal models for on‑device deployment
• Investigate, develop and apply advanced quantisation (8‑bit, 4‑bit, mixed precision), pruning, and distillation techniques for deriving optimised models for NXP NPU targets.
• Accelerate inference performance
• Investigate, develop and implement system optimisations such as speculative decoding and other efficient decoding algorithms tailored for edge environments.
• Engineer agentic AI capabilities towards tiny agents
• Investigate methodologies for enhancing the performance of small language models towards enabling tiny agents at the edge, while ensuring these follow safety principles.
• Work with inference engines and deployment frameworks
• Deploy optimised models using Ollama, llama.cpp, ONNX Runtime, and TFLite for efficient NPU inference.
• Benchmark LLMs and agentic systems
• Design benchmarking pipelines for assessing the performance of Generative and Agentic AI systems on‑device.
• Develop demonstrators and proof‑of‑concepts
• Move key technologies from research into product solutions

• MSc, PhD or EngD in a technical specialism, like Computer Science or equally relevant.
• 5+ years of experience in software/AI engineering with deep exposure to LLMs, VLMs, and systems performance.
• Experience with LLM quantisation techniques (e.g., Smooth Quant, Spin Quant, QuaRoT), pruning (Wanda, Sparse
  
  GPT, etc.) and other system optimisations like speculative decoding.
• Track‑record experience in working with AI frameworks (PyTorch, Tensor Flow, etc.), required.
• Experience with Agentic AI technologies and familiarity with existing frameworks (e.g., Lang Chain, Google ADK, Smol Agents, etc.)
• Understanding of safety and security considerations for agentic systems (e.g., guardrails, policy enforcement, secure function calling) is a plus.
• Understanding of AI tool chains, deployment, portability and inference engines (CUDA, Tensor
  
  RT, TFLite, ONNX, Ollama, etc.) preferred.
• Affinity and experience with embedded systems, and NPU accelerators required.
• Experience with embedded software architecture, build systems, version control systems required.
• Broad experience with Operating systems GNU/Linux, embedded systems, development boards, and processors, and SW competencies required.
• Familiarity with setting up and maintaining related ML‑Ops development environments (MLFlow, Clear
  
  ML, etc.) required.
• Knowledge of build systems (YOCTO, Open Embedded, etc.) beneficial, working with cross‑compilation tool chains for ARM preferred.
• Solid programming experience of C, C++, Python and Bash programming languages on Linux systems required.
• Excellent communication skills in English (verbal /written) required. Experience in working in/with multi‑site and multi‑cultural projects/teams preferred.